{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2c0d24bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import talib\n",
    "import yfinance as yf\n",
    "from talib import abstract\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "2f4cdd87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "data=yf.download('tsla',start='2020-1-1',end='2021-12-12')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6f46e86e",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['AROON']=talib.AROONOSC(data['High'],data['Low'],timeperiod=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "e60b5acf",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data[['Open','High','Low','Adj Close','Volume','AROON']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "3959f330",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.rename(columns={'Open':'open','High':'high','Low':'low','Adj Close':'close','Volume':'volume','AROON':'arron'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2bbb15fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['RSI'] = abstract.RSI(data)\n",
    "data['ADX']  = abstract.ADX(data, timeperiod=3)\n",
    "#data['APO'] = abstract.APO(data, 10, 20)\n",
    "data['CCI']  = abstract.ADX(data, timeperiod=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c0a1fc3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dfb43b70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter Ticker: tsla\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.plot(data.index,data['close'])\n",
    "plt.plot(data.index, data[data.columns[-1]])\n",
    "plt.plot(data.index, data[data.columns[-2]])\n",
    "plt.plot(data.index, data[data.columns[-3]])\n",
    "plt.title(\"Analysis of \" + input(\"Enter Ticker: \"))\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7889a2cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>RSI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>81.000000</td>\n",
       "      <td>84.258003</td>\n",
       "      <td>80.416000</td>\n",
       "      <td>83.666000</td>\n",
       "      <td>51428500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>84.900002</td>\n",
       "      <td>86.139999</td>\n",
       "      <td>84.342003</td>\n",
       "      <td>86.052002</td>\n",
       "      <td>47660500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>88.099998</td>\n",
       "      <td>90.800003</td>\n",
       "      <td>87.384003</td>\n",
       "      <td>88.601997</td>\n",
       "      <td>88892500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-06</th>\n",
       "      <td>88.094002</td>\n",
       "      <td>90.311996</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>90.307999</td>\n",
       "      <td>50665000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-07</th>\n",
       "      <td>92.279999</td>\n",
       "      <td>94.325996</td>\n",
       "      <td>90.671997</td>\n",
       "      <td>93.811996</td>\n",
       "      <td>89410500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-06</th>\n",
       "      <td>1001.510010</td>\n",
       "      <td>1021.640015</td>\n",
       "      <td>950.500000</td>\n",
       "      <td>1009.010010</td>\n",
       "      <td>27221000</td>\n",
       "      <td>43.607863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-07</th>\n",
       "      <td>1044.199951</td>\n",
       "      <td>1057.670044</td>\n",
       "      <td>1026.810059</td>\n",
       "      <td>1051.750000</td>\n",
       "      <td>18694900</td>\n",
       "      <td>48.926065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-08</th>\n",
       "      <td>1052.709961</td>\n",
       "      <td>1072.380005</td>\n",
       "      <td>1033.000000</td>\n",
       "      <td>1068.959961</td>\n",
       "      <td>13968800</td>\n",
       "      <td>50.932700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-09</th>\n",
       "      <td>1060.640015</td>\n",
       "      <td>1062.489990</td>\n",
       "      <td>1002.359985</td>\n",
       "      <td>1003.799988</td>\n",
       "      <td>19812800</td>\n",
       "      <td>43.900037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-10</th>\n",
       "      <td>1008.750000</td>\n",
       "      <td>1020.979980</td>\n",
       "      <td>982.530029</td>\n",
       "      <td>1017.030029</td>\n",
       "      <td>19855000</td>\n",
       "      <td>45.544154</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>492 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   open         high          low        close    volume  \\\n",
       "Date                                                                       \n",
       "2019-12-31    81.000000    84.258003    80.416000    83.666000  51428500   \n",
       "2020-01-02    84.900002    86.139999    84.342003    86.052002  47660500   \n",
       "2020-01-03    88.099998    90.800003    87.384003    88.601997  88892500   \n",
       "2020-01-06    88.094002    90.311996    88.000000    90.307999  50665000   \n",
       "2020-01-07    92.279999    94.325996    90.671997    93.811996  89410500   \n",
       "...                 ...          ...          ...          ...       ...   \n",
       "2021-12-06  1001.510010  1021.640015   950.500000  1009.010010  27221000   \n",
       "2021-12-07  1044.199951  1057.670044  1026.810059  1051.750000  18694900   \n",
       "2021-12-08  1052.709961  1072.380005  1033.000000  1068.959961  13968800   \n",
       "2021-12-09  1060.640015  1062.489990  1002.359985  1003.799988  19812800   \n",
       "2021-12-10  1008.750000  1020.979980   982.530029  1017.030029  19855000   \n",
       "\n",
       "                  RSI  \n",
       "Date                   \n",
       "2019-12-31        NaN  \n",
       "2020-01-02        NaN  \n",
       "2020-01-03        NaN  \n",
       "2020-01-06        NaN  \n",
       "2020-01-07        NaN  \n",
       "...               ...  \n",
       "2021-12-06  43.607863  \n",
       "2021-12-07  48.926065  \n",
       "2021-12-08  50.932700  \n",
       "2021-12-09  43.900037  \n",
       "2021-12-10  45.544154  \n",
       "\n",
       "[492 rows x 6 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "cell_type": "code",
   "execution_count": null,
   "id": "0db43b60",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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